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Introduction
The course is to introduce the principles of various fundamental machine learning techniques and their applications. It covers areas ranging from unsupervised learning to supervised learning as well as the various applications of machine learning that may be encountered in industry. Some examples and codes will be given.
Successful completion of the course will enable students to understand the principles of the classical machine learning methods.
2. Clustering: KNN, Chierarchical clustering
3. Regression: Linear regression, Kernelized regression
4. Performance evaluation
5. Classification: Tree, SVM and Multi-layer perceptron
6. Deep learning.
Data/Business/Financial Analyst who wish to gain more insights into machine learning skill sets.
Standard Course Fee: S$648.00
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SSG Funding Support |
Course fee |
Course fee payable after SSG funding, if eligible under various schemes |
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BEFORE funding & GST |
AFTER funding & 8% GST |
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Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) |
S$600.00 |
S$194.40 |
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Enhanced Training Support for SMEs (ETSS) |
S$74.40 |
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SCs aged ≥ 40 years old |
• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
Dr Adams Kong
Dr. Adams Wai Kin Kong received the Ph.D. degree from the University of Waterloo, Canada. Currently, he is an associate professor and the programme director of the Master of Science in Artificial Intelligence at the Nanyang Technological University, Singapore. His papers have been published in leading journals and conferences in his research areas, including TPAMI, TIP, TIFS, TCSVT, Pattern Recognition, CVPR, ICCV, ECCV, IJCAI, ICB and BTAS. One of his papers was selected as a spotlight paper by TPAMI and another was selected as Honorable Mention by Pattern Recognition. With his students, he received best student paper awards in The IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2012 and IEEE International Conference on Bioinformatics and Bioengineering, 2013. Dr. Kong received a number of awards for his research results. Currently, he is serving as an associate editor for IEEE Transactions on Information Forensics and Security. He has been working with industry partners, e.g., Rolls Royal, Procter & Gamble, Siemens and BAE systems for industrial research projects. He has developed ten patents. His research interests include pattern recognition, image processing, biometrics, and forensics.
